Download or read book Applied Software Development With Python Machine Learning By Wearable Wireless Systems For Movement Disorder Treatment Via Deep Brain Stimulation written by Robert Lemoyne and published by World Scientific. This book was released on 2021-08-26 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents the confluence of wearable and wireless inertial sensor systems, such as a smartphone, for deep brain stimulation for treating movement disorders, such as essential tremor, and machine learning. The machine learning distinguishes between distinct deep brain stimulation settings, such as 'On' and 'Off' status. This achievement demonstrates preliminary insight with respect to the concept of Network Centric Therapy, which essentially represents the Internet of Things for healthcare and the biomedical industry, inclusive of wearable and wireless inertial sensor systems, machine learning, and access to Cloud computing resources.Imperative to the realization of these objectives is the organization of the software development process. Requirements and pseudo code are derived, and software automation using Python for post-processing the inertial sensor signal data to a feature set for machine learning is progressively developed. A perspective of machine learning in terms of a conceptual basis and operational overview is provided. Subsequently, an assortment of machine learning algorithms is evaluated based on quantification of a reach and grasp task for essential tremor using a smartphone as a wearable and wireless accelerometer system.Furthermore, these skills regarding the software development process and machine learning applications with wearable and wireless inertial sensor systems enable new and novel biomedical research only bounded by the reader's creativity.Related Link(s)
Download or read book Applied Software Development With Python Machine Learning By Wearable Wireless Systems For Movement Disorder Treatment Via Deep Brain Stimulation written by Robert Charles LeMoyne and published by . This book was released on 2021 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The book presents the confluence of wearable and wireless inertial sensor systems, such as a smartphone, for deep brain stimulation for treating movement disorders, such as essential tremor, and machine learning. The machine learning distinguishes between distinct deep brain stimulation settings, such as 'On' and 'Off' status. This achievement demonstrates preliminary insight with respect to the concept of Network Centric Therapy, which essentially represents the Internet of Things for healthcare and the biomedical industry, inclusive of wearable and wireless inertial sensor systems, machine learning, and access to Cloud computing resources. Imperative to the realization of these objectives is the organization of the software development process. Requirements and pseudo code are derived, and software automation using Python for post-processing the inertial sensor signal data to a feature set for machine learning is progressively developed. A perspective of machine learning in terms of a conceptual basis and operational overview is provided. Subsequently, an assortment of machine learning algorithms is evaluated based on quantification of a reach and grasp task for essential tremor using a smartphone as a wearable and wireless accelerometer system. Furthermore, these skills regarding the software development process and machine learning applications with wearable and wireless inertial sensor systems enable new and novel biomedical research only bounded by the reader's creativity"--
Download or read book Wearable and Wireless Systems for Healthcare written by Robert LeMoyne and published by Springer Nature. This book was released on 2018 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Wearable and Wireless Systems for Healthcare II written by Robert LeMoyne and published by Springer. This book was released on 2019-02-20 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a far-sighted perspective on the role of wearable and wireless systems for movement disorder evaluation, such as Parkinson’s disease and Essential tremor. These observations are brought together in the application of quantified feedback for deep brain stimulation systems using the wireless accelerometer and gyroscope of a smartphone to determine tuning efficacy. The perspective of the book ranges from the pioneering application of these devices, such as the smartphone, for quantifying Parkinson’s disease and Essential tremor characteristics, to the current state of the art. Dr. LeMoyne has published multiple first-of-their-kind applications using smartphones to quantify movement disorder, with associated extrapolation to portable media devices.
Download or read book Wearable and Wireless Systems for Healthcare written by Robert Charles LeMoyne and published by . This book was released on 2019 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a far-sighted perspective on the role of wearable and wireless systems for movement disorder evaluation, such as Parkinson’s disease and Essential tremor. These observations are brought together in the application of quantified feedback for deep brain stimulation systems using the wireless accelerometer and gyroscope of a smartphone to determine tuning efficacy. The perspective of the book ranges from the pioneering application of these devices, such as the smartphone, for quantifying Parkinson’s disease and Essential tremor characteristics, to the current state of the art. Dr. LeMoyne has published multiple first-of-their-kind applications using smartphones to quantify movement disorder, with associated extrapolation to portable media devices.
Download or read book Machine Learning A Journey To Deep Learning With Exercises And Answers written by Andreas Miroslaus Wichert and published by World Scientific. This book was released on 2021-01-26 with total page 641 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning algorithms as well as to invent new machine learning methods. It tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students.Related Link(s)
Download or read book Deep Learning in Smart eHealth Systems written by Asma Channa and published by Springer Nature. This book was released on 2023-12-07 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the main benefits of this book is that it presents a comprehensive and innovative eHealth framework that leverages deep learning and IoT wearable devices for the evaluation of Parkinson's disease patients. This framework offers a new way to assess and monitor patients' motor deficits in a personalized and automated way, improving the efficiency and accuracy of diagnosis and treatment. Compared to other books on eHealth and Parkinson's disease, this book offers a unique perspective and solution to the challenges facing patients and healthcare providers. It combines state-of-the-art technology, such as wearable devices and deep learning algorithms, with clinical expertise to develop a personalized and efficient evaluation framework for Parkinson's disease patients. This book provides a roadmap for the integration of cutting-edge technology into clinical practice, paving the way for more effective and patient-centered healthcare. To understand this book, readers should have a basic knowledge of eHealth, IoT, deep learning, and Parkinson's disease. However, the book provides clear explanations and examples to make the content accessible to a wider audience, including researchers, practitioners, and students interested in the intersection of technology and healthcare.
Download or read book Digital Technologies in Movement Disorders written by and published by Elsevier. This book was released on 2023-07-24 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital Technologies in Movement Disorders, Volume Five updates on the latest advances in new technologies for the care of common conditions, including Parkinson’s disease and other diseases. The book has been organized in four differentiated sections with chapters that cover an Introduction, key concepts, and overview of digital solutions, Applications of AI in MD, Digital Biomarkers in MD, Sensors basic concepts for the MD specialist, Wearable systems in MD, Quantitative gait analysis, The challenges and opportunities of remote evaluation in MD, Telemedicine in MD, ePROs, eCOA and other digital health solutions, HIFU, Telerrehabilition and other therapeutical applications of technology, and more. Includes a multidisciplinary review of topics such as the input of care providers and engineers Reviews new technological advances Includes practice oriented technologies and innovations that have direct applications in the clinic
Download or read book Handbook of Digital Technologies in Movement Disorders written by Roongroj Bhidayasiri and published by Elsevier. This book was released on 2024-01-20 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past few years, there have been fundamental changes in the diagnosing and treating patients with chronic diseases, significantly affecting management of neurological movement disorders. In addition, the health and fitness sector developed several devices to better classify, track, and potentially treat chronic diseases. Both handling and interpreting these large datasets has been revolutionized, by machine and deep learning approaches, leading to new and more effective therapies, resulting in longer survival rates. Handbook of Digital Technologies in Movement Disorders aims to unite these factors to provide a comprehensive guide to patient focused treatments for movement disorders. This book is divided into five distinct sections, starting with an introduction to digital technologies, concepts, and terminologies. The following section reviews various perspectives on technology in movement disorders, including patient and medical professionals. The third section presents technologies used in detecting, measuring progression, and determining response to treatments. This is followed by reviewing the technology used in various treatments of movement disorders including assistive and robotic technologies. Finally, the last section examines the challenges with technology including privacy and other ethical issues. Reviews different stakeholders' perspectives on technology in movement disorders Presents technological advancements for diagnosing, monitoring, and managing Parkinson’s disease Discusses challenges with implementing technology into treatment
Download or read book Deep Learning in Biology and Medicine written by Davide Bacciu and published by World Scientific Publishing Europe Limited. This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biology, medicine and biochemistry have become data-centric fields for which Deep Learning methods are delivering groundbreaking results. Addressing high impact challenges, Deep Learning in Biology and Medicine provides an accessible and organic collection of Deep Learning essays on bioinformatics and medicine. It caters for a wide readership, ranging from machine learning practitioners and data scientists seeking methodological knowledge to address biomedical applications, to life science specialists in search of a gentle reference for advanced data analytics.With contributions from internationally renowned experts, the book covers foundational methodologies in a wide spectrum of life sciences applications, including electronic health record processing, diagnostic imaging, text processing, as well as omics-data processing. This survey of consolidated problems is complemented by a selection of advanced applications, including cheminformatics and biomedical interaction network analysis. A modern and mindful approach to the use of data-driven methodologies in the life sciences also requires careful consideration of the associated societal, ethical, legal and transparency challenges, which are covered in the concluding chapters of this book.
Download or read book Low power Wearable Healthcare Sensors written by R. Simon Sherratt and published by MDPI. This book was released on 2020-12-29 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in technology have produced a range of on-body sensors and smartwatches that can be used to monitor a wearer’s health with the objective to keep the user healthy. However, the real potential of such devices not only lies in monitoring but also in interactive communication with expert-system-based cloud services to offer personalized and real-time healthcare advice that will enable the user to manage their health and, over time, to reduce expensive hospital admissions. To meet this goal, the research challenges for the next generation of wearable healthcare devices include the need to offer a wide range of sensing, computing, communication, and human–computer interaction methods, all within a tiny device with limited resources and electrical power. This Special Issue presents a collection of six papers on a wide range of research developments that highlight the specific challenges in creating the next generation of low-power wearable healthcare sensors.
Download or read book DATA SCIENCE WORKSHOP Parkinson Classification and Prediction Using Machine Learning and Deep Learning with Python GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2023-07-26 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this data science workshop focused on Parkinson's disease classification and prediction, we begin by exploring the dataset containing features relevant to the disease. We perform data exploration to understand the structure of the dataset, check for missing values, and gain insights into the distribution of features. Visualizations are used to analyze the distribution of features and their relationship with the target variable, which is whether an individual has Parkinson's disease or not. After data exploration, we preprocess the dataset to prepare it for machine learning models. This involves handling missing values, scaling numerical features, and encoding categorical variables if necessary. We ensure that the dataset is split into training and testing sets to evaluate model performance effectively. With the preprocessed dataset, we move on to the classification task. Using various machine learning algorithms such as Logistic Regression, K-Nearest Neighbors, Decision Trees, Random Forests, Gradient Boosting, Naive Bayes, Adaboost, Extreme Gradient Boosting, Light Gradient Boosting, and Multi-Layer Perceptron (MLP), we train multiple models on the training data. To optimize the hyperparameters of these models, we utilize Grid Search, a technique to exhaustively search for the best combination of hyperparameters. For each machine learning model, we evaluate their performance on the test set using various metrics such as accuracy, precision, recall, and F1-score. These metrics help us understand the model's ability to correctly classify individuals with and without Parkinson's disease. Next, we delve into building an Artificial Neural Network (ANN) for Parkinson's disease prediction. The ANN architecture is designed with input, hidden, and output layers. We utilize the TensorFlow library to construct the neural network with appropriate activation functions, dropout layers, and optimizers. The ANN is trained on the preprocessed data for a fixed number of epochs, and we monitor its training and validation loss and accuracy to ensure proper training. After training the ANN, we evaluate its performance using the same metrics as the machine learning models, comparing its accuracy, precision, recall, and F1-score against the previous models. This comparison helps us understand the benefits and limitations of using deep learning for Parkinson's disease prediction. To provide a user-friendly interface for the classification and prediction process, we design a Python GUI using PyQt. The GUI allows users to load their own dataset, choose data preprocessing options, select machine learning classifiers, train models, and predict using the ANN. The GUI provides visualizations of the data distribution, model performance, and prediction results for better understanding and decision-making. In the GUI, users have the option to choose different data preprocessing techniques, such as raw data, normalization, and standardization, to observe how these techniques impact model performance. The choice of classifiers is also available, allowing users to compare different models and select the one that suits their needs best. Throughout the workshop, we emphasize the importance of proper evaluation metrics and the significance of choosing the right model for Parkinson's disease classification and prediction. We highlight the strengths and weaknesses of each model, enabling users to make informed decisions based on their specific requirements and data characteristics. Overall, this data science workshop provides participants with a comprehensive understanding of Parkinson's disease classification and prediction using machine learning and deep learning techniques. Participants gain hands-on experience in data preprocessing, model training, hyperparameter tuning, and designing a user-friendly GUI for efficient and effective data analysis and prediction.
Download or read book Wearable and Wireless Systems for Healthcare I written by Robert LeMoyne and published by Springer. This book was released on 2017-10-20 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides visionary perspective and interpretation regarding the role of wearable and wireless systems for the domain of gait and reflex response quantification. These observations are brought together in their application to smartphones and other portable media devices to quantify gait and reflex response in the context of machine learning for diagnostic classification and integration with the Internet of things and cloud computing. The perspective of this book is from the first-in-the-world application of these devices, as in smartphones, for quantifying gait and reflex response, to the current state of the art. Dr. LeMoyne has published multiple groundbreaking applications using smartphones and portable media devices to quantify gait and reflex response.
Download or read book Brain Computer Interfaces written by Desney S. Tan and published by Springer Science & Business Media. This book was released on 2010-06-10 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: For generations, humans have fantasized about the ability to create devices that can see into a person’s mind and thoughts, or to communicate and interact with machines through thought alone. Such ideas have long captured the imagination of humankind in the form of ancient myths and modern science fiction stories. Recent advances in cognitive neuroscience and brain imaging technologies have started to turn these myths into a reality, and are providing us with the ability to interface directly with the human brain. This ability is made possible through the use of sensors that monitor physical processes within the brain which correspond with certain forms of thought. Brain-Computer Interfaces: Applying our Minds to Human-Computer Interaction broadly surveys research in the Brain-Computer Interface domain. More specifically, each chapter articulates some of the challenges and opportunities for using brain sensing in Human-Computer Interaction work, as well as applying Human-Computer Interaction solutions to brain sensing work. For researchers with little or no expertise in neuroscience or brain sensing, the book provides background information to equip them to not only appreciate the state-of-the-art, but also ideally to engage in novel research. For expert Brain-Computer Interface researchers, the book introduces ideas that can help in the quest to interpret intentional brain control and develop the ultimate input device. It challenges researchers to further explore passive brain sensing to evaluate interfaces and feed into adaptive computing systems. Most importantly, the book will connect multiple communities allowing research to leverage their work and expertise and blaze into the future.
Download or read book Wearable Technologies in Organizations written by Aleksandra Przegalinska and published by Palgrave Pivot. This book was released on 2019-01-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This innovative book considers the positive and negative impact of wearable technologies on organization and work. First discussing the development and use of this software within the workspace, the author highlights potential issues such as privacy, addiction and lack of work efficiency. Technology has had a major impact on workspace and workforce, and the second section explores how it has emerged as a key driver of collaboration, and what the shortfalls are in terms of autonomy, solidarity and authenticity. Cloud technology, mobile technology, collaboration apps, the Internet of Things, and highly specialized AI bear the promise of a radical enhancement of the way we work and interact. This book discusses the potential future scenarios for wearable technologies in the context of the IoT and as a social and organizational phenomenon.
Download or read book Handbook of Large Scale Distributed Computing in Smart Healthcare written by Samee U. Khan and published by Springer. This book was released on 2017-08-07 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume offers readers various perspectives and visions for cutting-edge research in ubiquitous healthcare. The topics emphasize large-scale architectures and high performance solutions for smart healthcare, healthcare monitoring using large-scale computing techniques, Internet of Things (IoT) and big data analytics for healthcare, Fog Computing, mobile health, large-scale medical data mining, advanced machine learning methods for mining multidimensional sensor data, smart homes, and resource allocation methods for the BANs. The book contains high quality chapters contributed by leading international researchers working in domains, such as e-Health, pervasive and context-aware computing, cloud, grid, cluster, and big-data computing. We are optimistic that the topics included in this book will provide a multidisciplinary research platform to the researchers, practitioners, and students from biomedical engineering, health informatics, computer science, and computer engineering.
Download or read book Parkinson s Disease Management through ICT written by Joan Cabestany and published by CRC Press. This book was released on 2022-09-01 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parkinson's Disease (PD) is a neurodegenerative disorder that manifests with motor and non-motor symptoms. PD treatment is symptomatic and tries to alleviate the associated symptoms through an adjustment of the medication. As the disease is evolving and this evolution is patient specific, it could be very difficult to properly manage the disease.The current available technology (electronics, communication, computing, etc.), correctly combined with wearables, can be of great use for obtaining and processing useful information for both clinicians and patients allowing them to become actively involved in their condition.Parkinson's Disease Management through ICT: The REMPARK Approach presents the work done, main results and conclusions of the REMPARK project (2011 – 2015) funded by the European Union under contract FP7-ICT-2011-7-287677. REMPARK system was proposed and developed as a real Personal Health Device for the Remote and Autonomous Management of Parkinson’s Disease, composed of different levels of interaction with the patient, clinician and carers, and integrating a set of interconnected sub-systems: sensor, auditory cueing, Smartphone and server. The sensor subsystem, using embedded algorithmics, is able to detect the motor symptoms associated with PD in real time. This information, sent through the Smartphone to the REMPARK server, is used for an efficient management of the disease.
